The present disclosure relates generally to systems and methods for analyzing energy consumption model data. The present disclosure relates more particularly to systems and methods for determining an appropriate number of parameters (e.g., regression coefficients and/or balance point parameters) for a building energy use model.
Many buildings are equipped with a variety of energy-consuming equipment and devices. For example, a building may be equipped with heating, ventilation, and air conditioning (HVAC) equipment that consume energy to regulate the temperature, humidity, and/or air quality in the building. Other exemplary types of energy-consuming building equipment include lighting fixtures, security equipment, data networking infrastructure, and other such equipment.
The energy efficiency of buildings has become an area of interest in recent years. For an energy provider, a high energy efficiency of the buildings that it services helps to alleviate strains placed on the energy provider's electrical generation and transmission assets. For a building operator, a high energy efficiency corresponds to greater financial savings because less energy is consumed by the building.
One way to improve the energy efficiency of a building is through an accurate model of the building's energy use. An energy use model for a building typically predicts the building's total energy consumption as a function of one or more predictor variables and one or more model parameters. The number and type of parameters included in the energy use model may depend on the physical location of the building and other characteristics of the building site. It is often difficult and challenging to accurately determine an appropriate parameter order for a building energy use model.